On-line reaction monitoring with spectroscopic methods affords invaluable mechanistic information to optimize chemical processes. A continuous analysis of the reaction progress provides rate constants and rate laws. Thermodynamic parameters can be extracted from titrations monitored in situ to evaluate equilibria. Moreover, real-time analysis enables the detection of reactive intermediates and the description of multistep transformations. The utility of on-line spectroscopy, however, hinges on the ability to identify the species monitored in the reaction. Modern computational chemistry allows the prediction of spectra and the assignment of individual components within complex reaction mixtures. For example, density functional theory (DFT) predictions of vibrational spectra expand the capability of in situ FTIR and Raman to gain kinetic and structural information by connecting the vibrations of reactive intermediates with the corresponding functional groups. Similarly, full time-dependent (TD)-DFT calculations can estimate the electronic spectra of conjugated compounds and help correlate UV-Vis bands of minor components with their tentative structures. Advances in flow chemistry and processing software have allowed routine on-line reaction monitoring by NMR spectroscopy. The continuous recording of 1H-, 13C-, 19F- or 31P NMR spectra during a reaction often reveals a complex set of signals for each species. Accurate prediction of NMR chemical shifts using the DFT gauge including invariant atomic orbitals approximation, DFT-GIAO, supports the rigorous assignment of diagnostic signals to a given component or fleeting intermediates. This talk presents a series of case studies from the chemical development portfolio that highlight the benefits of combining on-line monitoring spectroscopy with first-principles spectral predictions to expedite process understanding.

Predicting spectra by computational methods: Applications in reaction monitoring

ACS Spring 2022

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